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Word Entropy-Based Approach to Detect Highly Variable Genetic Markers for Bacterial Genotyping.


ABSTRACT: Genotyping methods are used to distinguish bacterial strains from one species. Thus, distinguishing bacterial strains on a global scale, between countries or local districts in one country is possible. However, the highly selected bacterial populations (e.g., local populations in hospital) are typically closely related and low diversified. Therefore, currently used typing methods are not able to distinguish individual strains from each other. Here, we present a novel pipeline to detect highly variable genetic segments for genotyping a closely related bacterial population. The method is based on a degree of disorder in analyzed sequences that can be represented by sequence entropy. With the identified variable sequences, it is possible to find out transmission routes and sources of highly virulent and multiresistant strains. The proposed method can be used for any bacterial population, and due to its whole genome range, also non-coding regions are examined.

SUBMITTER: Nykrynova M 

PROVIDER: S-EPMC7886790 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Word Entropy-Based Approach to Detect Highly Variable Genetic Markers for Bacterial Genotyping.

Nykrynova Marketa M   Barton Vojtech V   Sedlar Karel K   Bezdicek Matej M   Lengerova Martina M   Skutkova Helena H  

Frontiers in microbiology 20210203


Genotyping methods are used to distinguish bacterial strains from one species. Thus, distinguishing bacterial strains on a global scale, between countries or local districts in one country is possible. However, the highly selected bacterial populations (e.g., local populations in hospital) are typically closely related and low diversified. Therefore, currently used typing methods are not able to distinguish individual strains from each other. Here, we present a novel pipeline to detect highly va  ...[more]

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